17 Modules
2 - 3 MonthsOverview
Course Description
Our data science course is crafted to introduce you to data analysis, predictive modeling, and cutting-edge analytics. Whether you’re a beginner or looking for the best data science courses, this program will advance your expertise with data science classes, enabling you to excel in data science online course environments and earn a data science certification course with placement support.
What you'll learn
- Data collection, cleaning, and preprocessing techniques
- Exploratory data analysis and data visualization
- Machine learning algorithms for predictive analytics
- Statistical and inferential analysis
- Big data tools and technologies
- End-to-end data science project development
Course Features:
- 100+ hours of live data science classes
- Access to industry mentors and career assistance
- Data science course with placement opportunities
- Data science certification course upon completion
- Flexible scheduling for working professionals
Course Content
Installation of Anaconda Prompt
Jupyter Notebook-An Overview
Shorcut Lkeys in Jupyter Notebook
Data Types in Python
Rules for Naming the Variables List, Tuple, Set, Dictionary
"Introduction to Files and directories Introduction to the command prompt or terminal paths"
Text files Reading from a text file Opening a file using `with`
If, else if and else condition
For and While Loop
Machine Learning Libraries Numpy-Hands on
Pandas-Hands on
Learn how to explore, visualize, and extract insights from data
Data Visualization
Matplotlib-Hands on
Seaborn hands on
You need to think statistically and to speak the language of your data
Measures of Central Tendency
Measures of Dispersion
IQR Statistics-Hands-On
Classification, Regression, Fine-tuning your model
Supervised Learning
Unsupervised Learning
Linear Regression
Metrics in Linear Regression Hands-on in Linear Regression
Logistic Regression
Metrics in Logistic Regression
Hands-on in Logistic Regression
Linear regression
Metrics for Linear regression
Introduction to Data Preprocessing Standardizing Data
Exploratory Data Analysis Missing Values Outliers
Standardization Mnormalization Feature Scaling and Selection
Decision Tree
Bagging
"Boosting Random Forest"
Neural Network
“Use data science packages, analysis, visualization, create model, extract pure data etc”
Excel Functions
Conditional Formatting
Pivot tables
Dashboards
Basics of database schema
Importance SQL Clauses
SQL Joins
Introduction to Power BI desktop
ETL pipeline in Power BI
Calculating fields with DAX
Visualising data with reports
AI functionalities of Power BI
